Job Description

Do you have exceptional data capabilities?

Would you like to join a Global leader in Legal Analytics and Technology?

The Machine Learning Engineer leads the design, development, deployment, and operation of large-scale, production-grade AI/ML systems

They drive the end-to-end lifecycle from research prototypes to highly reliable, scalable production systems define and standardize MLOps best practices, including training, evaluation, deployment, and monitoring pipelines and architect and evolve shared platforms and infrastructure for model training, evaluation, and low-latency inference at scale This role requires strong expertise in software engineering, distributed systems, and cloud-native architectures with deep experience in LLM/Generative AI systems (RAG, agents), retrieval/search systems, vector/graph databases, and modern MLOps platforms

Responsibilities

• Lead cross-functional collaboration with product, data science, and engineering teams to define and influence technical strategy and requirements
• Own and review system-level architecture and detailed technical designs for scalable AI/ML platforms
• Diagnoses and resolve critical, system-wide issues across ML pipelines, data infrastructure, and distributed production environments
• Translate ambiguous product requirements into scalable architectures, including LLM-based, RAG, and agent-driven systems
• Establish and enforce engineering best practices, code quality standards, and development processes across teams
• Lead resolution of high-impact technical challenges and provide technical mentorship to engineers
• Lead the design and productionization of LLM-based and Generative AI systems (e.g., RAG pipelines, multi-agent systems) at scale
• Design and optimize advanced agent capabilities (tool use, planning, reasoning, memory), ensuring robustness, observability, and reliability in production
• Drive integration of AI/ML services into enterprise ecosystems via scalable APIs and microservices architectures
• Collaborate with cross-functional teams to deliver high-impact AI-powered products and platform capabilities
• Define and maintain architectural documentation, APIs, and platform standards
• Establish evaluation frameworks, define KPIs, and continuously improve model and agent performance in production environments

Requirements

• Bachelor’s degree in computer science or related field (advanced degree preferred) or equivalent experience
• 10+ years of experience in software engineering and/or machine learning engineering, including leading large-scale systems
• Proven track record of driving adoption of new technologies and setting technical direction
• Deep experience with complex data models, large-scale datasets, and data-intensive systems
• Strong communication skills with ability to influence technical and non-technical stakeholders
• Strong system design and problem-solving skills with ability to navigate ambiguity
• Extensive experience designing, deploying, and operating LLM / Generative AI systems in production at scale
• Expertise in API design, system integration, and microservices-based architectures
• Experience leading and mentoring engineers in agile, cross-functional environments
• Strong foundation in SQL, data modeling, ML algorithms, and rigorous evaluation methodologies
• Extensive experience with large-scale distributed systems and data processing pipelines
• Hands-on expertise with cloud platforms (AWS, GCP, Azure), infrastructure-as-code, and mature CI/CD systems
• Expert-level programming skills in Python and proficiency in additional languages (e.g., Go, Rust)

Preferred / Highly Advantageous

• Deep expertise in NLP, including modern and classical techniques
• Hands-on experience with agent frameworks (OpenAI SDK, Anthropic SDK, Google ADK), RAG architectures, embeddings, and vector databases in production settings
• Experience designing and scaling CI/CD systems (Jenkins, GitHub Actions, Azure DevOps)
• Experience with Spark / Databricks and large-scale data platform architecture

Work in a way that works for you

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

Working for you:

"We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

• Medical and Life Insurance: Coverage for Medical and life risk.

• Long-Service Award: Recognition for loyalty and dedication.

• Marriage and New Baby Gifts: Celebratory tokens for special life events.

• Festivals and Birthday Gifts: Spreading joy on occasions that matter.

• Annual Medical Check-up: Prioritizing employee well-being through regular health check-ups.

• Flexible Benefits via CIIC Platform: Personalized benefits accessible through a user-friendly platform.

• Paid Time Off: Annual Leave, Flex Family Care Leave, Birthday Leave, Marriage Leave, Compassionate Leave, Medical and Hospitalization Leave, Examination Leave Gazetted Public Holiday

• Family Care leave (Maternity/Paternity Leave and Adoption Leave)"

About the Business

LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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